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Micro-sociology of violence looks at what happens in situations where people directly threaten violence, but only sometimes carry it out. This process and its turning points have become easier to see in the current era of visual data: cell-phone videos, long-distance telephoto lenses, CCTV cameras. New cues and instruments are on the horizon as we look at emotional signals, body rhythms, and monitors for body signs such as heart rate (a proxy for adrenaline level).

Building on an emerging literature concerning algorithmic management, this article analyzes the processes by which food delivery platforms control workers and uncovers variation in the extent to which such platforms constrain the freedoms—over schedules and activities—associated with gig work.

We run a randomized experiment to examine gender discrimination in book purchasing with 2,544 subjects on Amazon’s Mechanical Turk. We manipulate author gender and book genre in a factorial design to study consumer preferences for male versus female versus androgynous authorship. Despite previous findings in the literature showing gender discrimination in book publishing and in evaluations of work, respondents expressed no gender preference across a variety of measures, including quality, interest, and the amount they were willing to pay to purchase the book.

Protest event analysis is an important method for the study of collective action and social movements and typically draws on traditional media reports as the data source. We introduce collective action from social media (CASM)—a system that uses convolutional neural networks on image data and recurrent neural networks with long short-term memory on text data in a two-stage classifier to identify social media posts about offline collective action. We implement CASM on Chinese social media data and identify more than 100,000 collective action events from 2010 to 2017 (CASM-China).

The author argues that behind the apparent randomness of interactions between cabdrivers and their fares in Warsaw is a temporal structure. To capture this temporal structure, the author introduces the notion of a linking ecology. He argues that the Warsaw taxi market is a linking ecology, which is structured by religious time, state time, and family time. The author then focuses on waiting time, arguing that it too structures the interactions between cabdrivers and their fares.

Identity theory (IT) and social identity theory (SIT) are eminent research programs from sociology and psychology, respectively. We test collective identity as a point of convergence between the two programs. Collective identity is a subtheory of SIT that pertains to activist identification. Collective identity maps closely onto identity theory’s group/social identity, which refers to identification with socially situated identity categories. We propose conceptualizing collective identity as a type of group/social identity, integrating activist collectives into the identity theory model.

The structures of the tech industry, with its dependence on highly skilled immigrant workers, and the H-1B visa, with its dependence on sponsoring companies, bind tech workers in a cycle of legal violence.

The media and popular business press often invoke narratives that reflect widespread anxiety that robots may be rendering humans obsolete in the workplace. However, upon closer examination, many argue that automation, including robotics and artificial intelligence, is spreading unevenly throughout the labor market, such that middle-skill occupations that do not require a college degree are more likely to be affected adversely because they are easier to automate than high-skill occupations.

This paper documents and estimates the extent of underrepresentation of women and people of color on the pages of Wikipedia devoted to contemporary American sociologists. In contrast to the demographic diversity of the discipline, sociologists represented on Wikipedia are largely white men. The gender and racial/ethnic gaps in likelihood of representation have exhibited little change over time. Using novel data, we estimate the “risk” of having a Wikipedia page for a sample of contemporary sociologists.

This visualization provides a dynamic representation of the microsteps involved in modeling network and behavior change with a stochastic actor-based model. This video illustrates how (1) observed time is broken up into a series of simulated microsteps and (2) these microsteps serve as the opportunity for actors to change their network ties or behavior. The example model comes from a widely used tutorial, and we provide code to allow for adapting the visualization to one’s own model.